Market Context — Why This Technology, Why Now

The shift towards preventative healthcare and corporate wellness programs is accelerating, fueled by increasing awareness of sleep's impact on chronic diseases and mental health. Regulatory bodies are also encouraging data-driven health interventions. Companies seek non-invasive, scalable solutions to enhance employee well-being and reduce healthcare burdens, while consumers demand personalized health insights from accessible devices. This creates a strong market pull for precise, user-friendly sleep diagnostics.

Key Competitive Advantages
01

Achieves higher accuracy in sleep stage estimation by integrating body movement, heart rate, and respiration data to individually identify Awake, NREM, and REM stages.

02

Enables simple, non-invasive data acquisition, requiring no specialized medical equipment and reducing user burden for daily sleep monitoring.

03

Enhances determination reliability and robustness by using a unique logic that sets thresholds based on integrated body movement, heart rate, and respiration data.

Market Opportunity
Medical and Healthcare
$3B–$3.5B globally (AI est.)
This technology could enhance efficiency in medical settings and reduce patient burden by assisting in sleep disorder diagnosis, monitoring treatment efficacy, and integrating into telehealth services.
Digital health platform providers Medical device manufacturers Telemedicine service providers Hospital systems
Corporate Wellness Programs
$1.5B–$2B globally (AI est.)
By visualizing employee sleep quality and integrating with corporate health initiatives, this technology could boost productivity, reduce turnover rates, and improve corporate image.
Corporate wellness solution providers HR technology platforms Large employers with self-funded health plans
Smart Home and Elderly Care
$1B–$1.5B globally (AI est.)
Non-contact sleep monitoring for elderly care services could enhance safety and reduce caregiver burden, providing peace of mind for families.
Smart home device manufacturers Elderly care service providers Home automation companies
Sports and Fitness Optimization
$0.5B–$1B globally (AI est.)
This technology could optimize sleep for athletes, aiding recovery and performance enhancement to maximize training effectiveness.
Sports performance analytics companies Fitness wearable brands Professional sports organizations
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a robust method and device for high-accuracy sleep stage determination using integrated biometric data (body movement, heart rate, respiration). It successfully overcame an initial rejection, indicating a well-defined and stable scope of claims that provides strong defense against future invalidation challenges, offering licensees clear freedom to operate.

Competitive White Space

This patent primarily covers sleep stage detection. White space exists in developing personalized sleep intervention systems, integrating with smart home environmental controls, or applying the technology for pharmaceutical efficacy testing.

Economic Impact
~$200K/year estimated in healthcare cost and productivity loss reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

For a company with 1,000 employees, assuming annual personnel costs of ~$33.5M (AI est.), a 0.5% productivity improvement from better sleep could yield ~$167.5K/year (AI est.). Including healthcare cost reductions from early detection of sleep-related issues, total annual savings and value creation could exceed ~$200K (AI est.).

Speed to Market
6× faster than in-house development
This technology leverages data from common biometric sensors (body movement, heart rate, respiration), ensuring high compatibility with existing wearable devices and smart home equipment. The sleep stage determination algorithm is fully defined in the patent claims, indicating a well-established foundational technology. This enables licensees to significantly reduce R&D timelines, rapidly integrate functions into existing products, or develop new services for swift market entry.
Competitive Positioning

X: Precision and Simplicity
Y: Deployment & Operational Cost Efficiency

Business Models & Applications
📱 Device Embedded Licensing
This licensing model allows integration of this technology into existing wearable devices and IoT equipment, such as smartwatches, smart rings, and non-contact sensors. It provides high-accuracy sleep monitoring as added value, strengthening product competitiveness.
☁️ Healthcare SaaS Provision
Offer a sleep analysis platform powered by this technology as a SaaS, providing monthly subscription services to corporations and healthcare institutions. Deliver personalized sleep reports and improvement programs for recurring revenue.
📊 Data Analysis & Consulting
Based on acquired sleep data, analyze individual health status and group trends to offer specialized consulting services. Provide concrete advice for resolving sleep issues, developing high-value businesses.
Adjacent Application Opportunities
🚗 Automotive & Transportation
Driver Fatigue and Drowsiness Detection System
This technology could analyze real-time body movement, heart rate, and respiration data during driving to estimate driver alertness and fatigue levels. Early detection of drowsiness signs and issuing warnings could prevent accidents and enhance driving safety, potentially reducing incidents by 15-20%.
👶 Childcare & Baby Tech
Infant Sleep Monitoring and SIDS Prevention
By integrating non-contact sensors into infant beds or clothing, this technology could acquire body movement and respiration data to monitor sleep states. This application is expected to reduce the risk of SIDS (Sudden Infant Death Syndrome) and alleviate parental anxiety, offering a safer monitoring service.
🤖 Robotics & AI
Biometric-Linked Personal AI Assistant
Integrating sleep stage data from this technology with personal AI assistants could provide optimized information and lifestyle advice tailored to a user's sleep rhythm. This enables more personalized services, such as news delivery based on waking mood or environmental control to improve sleep quality, potentially boosting user engagement by over 25%.
Integration Roadmap — Estimated 18-Month Deployment
Technology Validation and PoC
Duration: 4 months
Acquire data from existing biometric sensors (body movement, heart rate, respiration) and implement/validate the sleep stage determination algorithm. Conduct small-scale Proof of Concept (PoC) to assess technical feasibility and performance.
Prototype Development and Testing
Duration: 6 months
Develop a prototype tailored to specific use cases based on PoC results. Design user interfaces, build data integration systems, and conduct detailed testing and iterative improvements in real-world environments.
Production Deployment and Optimization
Duration: 8 months
Deploy the developed system into a production environment and commence operations. Continuously optimize algorithms and expand functionalities based on ongoing data collection and feedback to enhance market fit.
Technical Feasibility
This technology utilizes common biometric data (body movement, heart rate, respiration), making it easily implementable across various hardware, including existing wearable devices, non-contact sensors, and smart beds. The data processing and determination logic described in the patent claims are software-implementable, allowing for integration into existing systems as a feature add-on without significant capital investment. This implies relatively low technical hurdles and rapid deployment potential.
Success Scenario
If integrated into an employee health management program, this technology could non-invasively provide detailed sleep patterns for individual employees. This may enable early identification of productivity losses due to poor sleep quality and the provision of personalized improvement strategies, potentially enhancing employee engagement and health, and contributing to an estimated average of 10% annual productivity improvement.
Patent Record
APPLICATION NO.
特願2020-019989
REGISTRATION NO.
6925056
FILING DATE
2020/02/07
GRANT DATE
2021/08/05
EXPIRATION DATE
2040/02/07
PATENT HOLDER
国立大学法人電気通信大学
Examination History
2020年02月07日
出願審査請求書
2021年01月19日
拒絶理由通知書
2021年05月20日
手続補正書（自発・内容）
2021年05月20日
意見書
2021年07月13日
特許査定